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《Journal of Tsinghua University(Science and Technology)》 2009-06
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Discovering functional dependencies with degrees of satisfaction using attribute pre-scanning

WEI Qiang,ZHOU Xiaocang(Department of Management Science and Engineering,School of Economics and Management,Tsinghua University,Beijing 100084,China)  
The functional dependency(FD) is a key constraint knowledge in relational databases and data modeling.However,noisy data and low efficiencies restrict the ability to mine functional dependencies in massive databases.Functional dependencies with degrees of satisfaction were used to discover minimal sets of functional dependencies(MFDD).The method not only measures the noises,but also efficiently discovers the minimal set of functional dependencies.A degree of diversity was used with a pre-scanning operation to evaluate the attribute value diversity to develop three optimization strategies for the functional dependency with a degree of satisfaction.Both theoretical analyses and test results show that the algorithm significantly improves the mining efficiency.
【Fund】: 国家自然科学基金资助项目(70231010 70621061)
【CateGory Index】: TP311.13
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